A number of methods do not model the robot dynamics explicitly. These approaches fall into two broad groups, those that utilize expert demonstrations [1]}, [2]}, [3]}, [4]}, [5]} and those that do not [6]}, [7]}, [8]}, [9]}. Like our best performing method, [5]} is capable of learning from sub-optimal demonstrations. However, the approach has no mechanism to continuously improve beyond the demonstration data. In [2]}, authors demonstrate a system that learns cooperative table tennis by creating a library of primitive motions using kinesthetic teaching to constrain learning. In a similar spirit, we collect an initial dataset of non-goal-directed demonstration data of how to make contact and return the ball to bootstrap autonomous learning.
